New research published by Amazon Web Services (AWS) and Telecom Advisory Services report that in 2023, cloud adoption overall contributed more than $1 trillion to the global GDP. AWS also projects that the global GDP based on cloud adoption will surpass $12 trillion by 2030.
However, this shift to the cloud also means that data – the driving force of virtually every business – is more vulnerable than ever before. With new opportunities and advancements come new responsibilities. To ensure business continuity, data privacy, and effective collaboration in a cloud-first world, it is imperative that the cloud environment is secure and well-governed.
In this article, we’ll dive deeper into the move toward cloud-native and multi-cloud environments, uncover some emerging trends in data governance, and reveal practical steps to stay ahead of the many regulatory changes coming our way.
The Shift to Cloud-Native Environments
The rapid evolution of technology is driving a fundamental shift in how organizations manage their IT infrastructure. As companies embrace this digital transformation, they are increasingly moving toward cloud-native and multi-cloud environments. Gartner predicts that worldwide public cloud end-user spending could reach $723 billion in 2025.
The transition to cloud environments offers numerous advantages, from increased flexibility and scalability to IT cost savings. Most companies agree, with 89% of organizations reported to use multiple cloud services. However, this shift also highlights critical challenges. In fact, 90% of organizations report facing difficulties in their cloud adoption journeys. One major hurdle is that traditional data governance models become less effective in these new settings. Why? The dynamic and distributed nature of the cloud requires a more agile and scalable approach to data governance.
40% of data breaches involved data stored across multiple environments, and 95% of organizations are moderately to extremely concerned about security in cloud environments. The proliferation of sharing options in cloud services only exacerbates this concern, due to the increased likelihood of inappropriate sharing and potential breaches. The presence of third-party access for system management can also introduce more compliance and privacy risks.
Capital One, for example, became the first US bank to announce its migration to the cloud — a move that took eight years to complete. In the heavily regulated financial services industry, managing vast amounts of sensitive financial data can cause significant hurdles. By leveraging AWS cloud services and implementing robust security measures, Capital One was able to enhance operational efficiency, reduce transaction errors, and innovate rapidly while maintaining compliance and safeguarding customer data.
Emerging Trends in Data Governance
To address these challenges associated with transitioning to cloud-native and multi-cloud environments, organizations with data across platforms like Microsoft, Google, AWS, and Salesforce (or any combination of these clouds) are reshaping their data governance strategies.
This change has brought forth emerging trends that promise to not only transform how we manage and protect data but also to help organizations stay competitive in today’s market and compliant with quickly evolving regulations. Trends include:
- AI-driven automation. AI-driven automation streamlines repetitive tasks such as data classification, access controls, and anomaly detection. This not only reduces manual efforts but also enhances accuracy and compliance.
- Decentralized control. Data governance responsibilities are distributed across various departments rather than being centralized. This approach allows for more localized and context-specific governance, improving responsiveness and compliance.
- Data privacy by design. Incorporating data privacy principles from the outset of system design ensures that privacy considerations are being integrated into every stage of data processing, reducing the risk of breaches and non-compliance.
- Real-time compliance monitoring. With the advent of data analytics and AI, organizations can now continuously monitor their data practices and immediately address any compliance issues as they arise.
- Data sovereignty. As data regulations become more stringent globally, data sovereignty – ensuring that organizations store and process data within specific geographic boundaries – is gaining importance. This is particularly relevant for multinational organizations needing to comply with diverse regulatory requirements
Recognizing how these new trends are reshaping data governance is just the beginning. To truly benefit from the shift to the cloud, it’s essential to adopt practical measures that not only address current needs but also anticipate future regulatory changes. Organizations must be proactive in their approach to data governance to ensure they stay compliant, secure, and competitive.
Practical Steps to Stay Ahead of Regulatory Changes
Complying with global privacy regulations isn’t just a precaution; non-compliance can also result in significant financial penalties (as evidenced by Meta’s whopping $1.3 billion fine for violating the GDPR). Staying ahead of regulatory changes is crucial for organizations to avoid these hefty penalties and maintain trust with stakeholders.
Proactively implementing data governance strategies is mission-critical when it comes to navigating the complex regulatory landscape efficiently. Businesses should consider the following key strategies:
- Conduct regular audits and assessments. Conduct regular audits and assessments to identify compliance gaps and areas for improvement. This proactive approach helps with staying ahead of evolving regulations and mitigating risks.
- Adopt advanced compliance tools. Utilize tools that offer real-time monitoring, automated reporting, and risk-assessment capabilities. These tools can help streamline compliance processes and reduce the burden on compliance teams.
- Develop a comprehensive data governance framework. Create a robust data governance framework that outlines policies, procedures, roles, and responsibilities. This framework should be flexible enough to adapt as regulations change and business needs evolve — and should be flexible enough to be applied to data that resides in multiple clouds.
- Leverage AI and machine learning (ML). Use AI and ML to enhance your existing data governance practices. These technologies can help automate compliance tasks, identify potential risks, and provide actionable insights for better decision-making.
- Invest in employee training and awareness. Invest in continuous training programs to keep team members informed about the latest regulations and best practices in data governance. An informed workforce is crucial for maintaining compliance.
Building a Resilient Future
Data governance is essential for organizations operating in a cloud-first world. By embracing modern data governance practices, businesses can secure their data, stay compliant, and collaborate more effectively than ever before.
The proactive adoption of the strategies discussed here helps ensure long-term success and resilience. A robust data governance framework is not just a regulatory necessity, but a strategic asset that drives competitive advantage — and helps organizations move faster with the proper guardrails in place, opening new opportunities for innovation and growth.
